arXiv - QuantFin - General Finance最新文献_第9页

Growth, Poverty Trap and Escape 增长、贫困陷阱和逃离

arXiv - QuantFin - General Finance Pub Date : 2023-10-13 DOI: arxiv-2310.09098

Indrani Bose

{"title":"Growth, Poverty Trap and Escape","authors":"Indrani Bose","doi":"arxiv-2310.09098","DOIUrl":"https://doi.org/arxiv-2310.09098","url":null,"abstract":"The well-known Solow growth model is the workhorse model of the theory of\u0000economic growth, which studies capital accumulation in a model economy as a\u0000function of time with capital stock, labour and technology efiiciency as the\u0000basic ingredients. The capital is assumed to be in the form of manufacturing\u0000equipments and materials. Two important parameters of the model are: the saving\u0000fraction $s$ of the output of a production function and the technology\u0000efficiency parameter $A$, appearing in the production function. The saved\u0000fraction of the output is fully invested in the generation of new capital and\u0000the rest is consumed. The capital stock also depreciates as a function of time\u0000due to the wearing out of old capital and the increase in the size of the\u0000labour population. We propose a stochastic Solow growth model assuming the\u0000saving fraction to be a sigmoidal function of the per capita capital $k_p$. We\u0000derive analytically the steady state probability distribution $P(k_p)$ and\u0000demonstrate the existence of a poverty trap, of central concern in development\u0000economics. In a parameter regime, $P(k_p)$ is bimodal with the twin peaks\u0000corresponding to states of poverty and well-being respectively. The associated\u0000potential landscape has two valleys with fluctuation-driven transitions between\u0000them. The mean exit times from the valleys are computed and one finds that the\u0000escape from a poverty trap is more favourable at higher values of $A$. We\u0000identify a critical value of $A_c$ below (above) which the state of poverty\u0000(well-being) dominates and propose two early signatures of the regime shift\u0000occurring at $A_c$. The economic model, with conceptual foundation in nonlinear\u0000dynamics and statistical mechanics, share universal features with dynamical\u0000models from diverse disciplines like ecology and cell biology.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138523136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams GPT模型能成为金融分析师吗?模拟CFA考试中ChatGPT和GPT-4的评价

arXiv - QuantFin - General Finance Pub Date : 2023-10-12 DOI: arxiv-2310.08678

Ethan Callanan, Amarachi Mbakwe, Antony Papadimitriou, Yulong Pei, Mathieu Sibue, Xiaodan Zhu, Zhiqiang Ma, Xiaomo Liu, Sameena Shah

引用次数: 0

Valuation Duration of the Stock Market 股票市场的估值持续时间

arXiv - QuantFin - General Finance Pub Date : 2023-10-11 DOI: arxiv-2310.07110

Ye Li, Chen Wang

引用次数: 0

Market Crowds' Trading Behaviors, Agreement Prices, and the Implications of Trading Volume 市场人群的交易行为、协议价格和交易量的影响

arXiv - QuantFin - General Finance Pub Date : 2023-10-09 DOI: arxiv-2310.05322

Leilei Shi, Bing Han, Yingzi Zhu, Liyan Han, Yiwen Wang, Yan Piao

{"title":"Market Crowds' Trading Behaviors, Agreement Prices, and the Implications of Trading Volume","authors":"Leilei Shi, Bing Han, Yingzi Zhu, Liyan Han, Yiwen Wang, Yan Piao","doi":"arxiv-2310.05322","DOIUrl":"https://doi.org/arxiv-2310.05322","url":null,"abstract":"It has been long that literature in financial academics focuses mainly on\u0000price and return but much less on trading volume. In the past twenty years, it\u0000has already linked both price and trading volume to economic fundamentals, and\u0000explored the behavioral implications of trading volume such as investor's\u0000attitude toward risks, overconfidence, disagreement, and attention etc.\u0000However, what is surprising is how little we really know about trading volume.\u0000Here we show that trading volume probability represents the frequency of market\u0000crowd's trading action in terms of behavior analysis, and test two adaptive\u0000hypotheses relevant to the volume uncertainty associated with price in China\u0000stock market. The empirical work reveals that market crowd trade a stock in\u0000efficient adaptation except for simple heuristics, gradually tend to achieve\u0000agreement on an outcome or an asset price widely on a trading day, and generate\u0000such a stationary equilibrium price very often in interaction and competition\u0000among themselves no matter whether it is highly overestimated or\u0000underestimated. This suggests that asset prices include not only a fundamental\u0000value but also private information, speculative, sentiment, attention, gamble,\u0000and entertainment values etc. Moreover, market crowd adapt to gain and loss by\u0000trading volume increase or decrease significantly in interaction with\u0000environment in any two consecutive trading days. Our results demonstrate how\u0000interaction between information and news, the trading action, and return\u0000outcomes in the three-term feedback loop produces excessive trading volume\u0000which includes various internal and external causes.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combining Deep Learning and GARCH Models for Financial Volatility and Risk Forecasting 结合深度学习和GARCH模型的金融波动和风险预测

arXiv - QuantFin - General Finance Pub Date : 2023-10-02 DOI: arxiv-2310.01063

Jakub Michańków, Łukasz Kwiatkowski, Janusz Morajda

{"title":"Combining Deep Learning and GARCH Models for Financial Volatility and Risk Forecasting","authors":"Jakub Michańków, Łukasz Kwiatkowski, Janusz Morajda","doi":"arxiv-2310.01063","DOIUrl":"https://doi.org/arxiv-2310.01063","url":null,"abstract":"In this paper, we develop a hybrid approach to forecasting the volatility and\u0000risk of financial instruments by combining common econometric GARCH time series\u0000models with deep learning neural networks. For the latter, we employ Gated\u0000Recurrent Unit (GRU) networks, whereas four different specifications are used\u0000as the GARCH component: standard GARCH, EGARCH, GJR-GARCH and APARCH. Models\u0000are tested using daily logarithmic returns on the S&P 500 index as well as gold\u0000price Bitcoin prices, with the three assets representing quite distinct\u0000volatility dynamics. As the main volatility estimator, also underlying the\u0000target function of our hybrid models, we use the price-range-based Garman-Klass\u0000estimator, modified to incorporate the opening and closing prices. Volatility\u0000forecasts resulting from the hybrid models are employed to evaluate the assets'\u0000risk using the Value-at-Risk (VaR) and Expected Shortfall (ES) at two different\u0000tolerance levels of 5% and 1%. Gains from combining the GARCH and GRU\u0000approaches are discussed in the contexts of both the volatility and risk\u0000forecasts. In general, it can be concluded that the hybrid solutions produce\u0000more accurate point volatility forecasts, although it does not necessarily\u0000translate into superior VaR and ES forecasts.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"308 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling the yield curve of Burundian bond market by parametric models 用参数化模型对布隆迪债券市场收益率曲线进行建模

arXiv - QuantFin - General Finance Pub Date : 2023-09-30 DOI: arxiv-2310.00321

Rédempteur Ntawiratsa, David Niyukuri, Irène Irakoze, Menus Nkurunziza

{"title":"Modeling the yield curve of Burundian bond market by parametric models","authors":"Rédempteur Ntawiratsa, David Niyukuri, Irène Irakoze, Menus Nkurunziza","doi":"arxiv-2310.00321","DOIUrl":"https://doi.org/arxiv-2310.00321","url":null,"abstract":"The term structure of interest rates (yield curve) is a critical facet of\u0000financial analytics, impacting various investment and risk management\u0000decisions. It is used by the central bank to conduct and monitor its monetary\u0000policy. That instrument reflects the anticipation of inflation and the risk by\u0000investors. The rates reported on yield curve are the cornerstone of valuation\u0000of all assets. To provide such tool for Burundi financial market, we collected\u0000the auction reports of treasury securities from the website of the Central Bank\u0000of Burundi. Then, we computed the zero-coupon rates, and estimated actuarial\u0000rates of return by applying the Nelson-Siegel and Svensson models. This paper\u0000conducts a rigorous comparative analysis of these two prominent parametric\u0000yield curve models and finds that the Nelson-Siegel model is the optimal choice\u0000for modeling the Burundian yield curve. The findings contribute to the body of\u0000knowledge on yield curve modeling, enhancing its precision and applicability in\u0000financial markets. Furthermore, this research holds implications for investment\u0000strategies, risk management, second market pricing, financial decision-making,\u0000and the forthcoming establishment of the Burundian stock market.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"205 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A systematic review of early warning systems in finance 对金融早期预警系统的系统回顾

arXiv - QuantFin - General Finance Pub Date : 2023-09-30 DOI: arxiv-2310.00490

Ali Namaki, Reza Eyvazloo, Shahin Ramtinnia

{"title":"A systematic review of early warning systems in finance","authors":"Ali Namaki, Reza Eyvazloo, Shahin Ramtinnia","doi":"arxiv-2310.00490","DOIUrl":"https://doi.org/arxiv-2310.00490","url":null,"abstract":"Early warning systems (EWSs) are critical for forecasting and preventing\u0000economic and financial crises. EWSs are designed to provide early warning signs\u0000of financial troubles, allowing policymakers and market participants to\u0000intervene before a crisis expands. The 2008 financial crisis highlighted the\u0000importance of detecting financial distress early and taking preventive measures\u0000to mitigate its effects. In this bibliometric review, we look at the research\u0000and literature on EWSs in finance. Our methodology included a comprehensive\u0000examination of academic databases and a stringent selection procedure, which\u0000resulted in the final selection of 616 articles published between 1976 and\u00002023. Our findings show that more than 90% of the papers were published after\u00002006, indicating the growing importance of EWSs in financial research.\u0000According to our findings, recent research has shifted toward machine learning\u0000techniques, and EWSs are constantly evolving. We discovered that research in\u0000this area could be divided into four categories: bankruptcy prediction, banking\u0000crisis, currency crisis and emerging markets, and machine learning forecasting.\u0000Each cluster offers distinct insights into the approaches and methodologies\u0000used for EWSs. To improve predictive accuracy, our review emphasizes the\u0000importance of incorporating both macroeconomic and microeconomic data into EWS\u0000models. To improve their predictive performance, we recommend more research\u0000into incorporating alternative data sources into EWS models, such as social\u0000media data, news sentiment analysis, and network analysis.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"34 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis GPT情绪分析在股票收益预测中的预估偏差

arXiv - QuantFin - General Finance Pub Date : 2023-09-29 DOI: arxiv-2309.17322

Paul Glasserman, Caden Lin

{"title":"Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis","authors":"Paul Glasserman, Caden Lin","doi":"arxiv-2309.17322","DOIUrl":"https://doi.org/arxiv-2309.17322","url":null,"abstract":"Large language models (LLMs), including ChatGPT, can extract profitable\u0000trading signals from the sentiment in news text. However, backtesting such\u0000strategies poses a challenge because LLMs are trained on many years of data,\u0000and backtesting produces biased results if the training and backtesting periods\u0000overlap. This bias can take two forms: a look-ahead bias, in which the LLM may\u0000have specific knowledge of the stock returns that followed a news article, and\u0000a distraction effect, in which general knowledge of the companies named\u0000interferes with the measurement of a text's sentiment. We investigate these\u0000sources of bias through trading strategies driven by the sentiment of financial\u0000news headlines. We compare trading performance based on the original headlines\u0000with de-biased strategies in which we remove the relevant company's identifiers\u0000from the text. In-sample (within the LLM training window), we find,\u0000surprisingly, that the anonymized headlines outperform, indicating that the\u0000distraction effect has a greater impact than look-ahead bias. This tendency is\u0000particularly strong for larger companies--companies about which we expect an\u0000LLM to have greater general knowledge. Out-of-sample, look-ahead bias is not a\u0000concern but distraction remains possible. Our proposed anonymization procedure\u0000is therefore potentially useful in out-of-sample implementation, as well as for\u0000de-biased backtesting.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Handling missing data in Burundian sovereign bond market 处理布隆迪主权债券市场缺失数据

arXiv - QuantFin - General Finance Pub Date : 2023-09-29 DOI: arxiv-2309.17379

Irène Irakoze, Rédempteur Ntawiratsa, David Niyukuri

{"title":"Handling missing data in Burundian sovereign bond market","authors":"Irène Irakoze, Rédempteur Ntawiratsa, David Niyukuri","doi":"arxiv-2309.17379","DOIUrl":"https://doi.org/arxiv-2309.17379","url":null,"abstract":"Constructing an accurate yield curve is essential for evaluating financial\u0000instruments and analyzing market trends in the bond market. However, in the\u0000case of the Burundian sovereign bond market, the presence of missing data poses\u0000a significant challenge to accurately constructing the yield curve. In this\u0000paper, we explore the limitations and data availability constraints specific to\u0000the Burundian sovereign market and propose robust methodologies to effectively\u0000handle missing data. The results indicate that the Linear Regression method,\u0000and the Previous value method perform consistently well across variables,\u0000approximating a normal distribution for the error values. The non parametric\u0000Missing Value Imputation using Random Forest (miss-Forest) method performs well\u0000for coupon rates but poorly for bond prices, and the Next value method shows\u0000mixed results. Ultimately, the Linear Regression (LR) method is recommended for\u0000imputing missing data due to its ability to approximate normality and\u0000predictive capabilities. However, filling missing values with previous values\u0000has high accuracy, thus, it will be the best choice when we have less\u0000information to be able to increase accuracy for LR. This research contributes\u0000to the development of financial products, trading strategies, and overall\u0000market development in Burundi by improving our understanding of the yield curve\u0000dynamics.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient? 评估虚拟资产服务提供商的偿付能力:现行标准是否足够?

arXiv - QuantFin - General Finance Pub Date : 2023-09-28 DOI: arxiv-2309.16408

Pietro Saggese, Esther Segalla, Michael Sigmund, Burkhard Raunig, Felix Zangerl, Bernhard Haslhofer

{"title":"Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient?","authors":"Pietro Saggese, Esther Segalla, Michael Sigmund, Burkhard Raunig, Felix Zangerl, Bernhard Haslhofer","doi":"arxiv-2309.16408","DOIUrl":"https://doi.org/arxiv-2309.16408","url":null,"abstract":"Entities like centralized cryptocurrency exchanges fall under the business\u0000category of virtual asset service providers (VASPs). As any other enterprise,\u0000they can become insolvent. VASPs enable the exchange, custody, and transfer of\u0000cryptoassets organized in wallets across distributed ledger technologies\u0000(DLTs). Despite the public availability of DLT transactions, the cryptoasset\u0000holdings of VASPs are not yet subject to systematic auditing procedures. In\u0000this paper, we propose an approach to assess the solvency of a VASP by\u0000cross-referencing data from three distinct sources: cryptoasset wallets,\u0000balance sheets from the commercial register, and data from supervisory\u0000entities. We investigate 24 VASPs registered with the Financial Market\u0000Authority in Austria and provide regulatory data insights such as who are the\u0000customers and where do they come from. Their yearly incoming and outgoing\u0000transaction volume amount to 2 billion EUR for around 1.8 million users. We\u0000describe what financial services they provide and find that they are most\u0000similar to traditional intermediaries such as brokers, money exchanges, and\u0000funds, rather than banks. Next, we empirically measure DLT transaction flows of\u0000four VASPs and compare their cryptoasset holdings to balance sheet entries.\u0000Data are consistent for two VASPs only. This enables us to identify gaps in the\u0000data collection and propose strategies to address them. We remark that any\u0000entity in charge of auditing requires proof that a VASP actually controls the\u0000funds associated with its on-chain wallets. It is also important to report fiat\u0000and cryptoasset and liability positions broken down by asset types at a\u0000reasonable frequency.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138543769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0